Nvidia has released a new mathematical Python library specialized for Cuda-X. It offers direct, Python-like access to the mathematical core operations of Cuda-X without having to use additional C/C++ ...

AI developers use popular frameworks like TensorFlow, PyTorch, and JAX to work on their projects. All these frameworks, in turn, rely on Nvidia's CUDA AI toolkit and libraries for high-performance AI ...

Today Nvidia announced that growing ranks of Python users can now take full advantage of GPU acceleration for HPC and Big Data analytics applications by using the CUDA parallel programming model. As a ...

Nvidia has placed Warp under an Apache 2 license. The Python framework is used for performance-hungry physical simulations, data generation and spatial computing. It compiles Python functions just in ...

CUDA enables faster AI processing by allowing simultaneous calculations, giving Nvidia a market lead. Nvidia's CUDA platform is the foundation of many GPU-accelerated applications, attracting ...

Why it matters: Nvidia introduced CUDA in 2006 as a proprietary API and software layer that eventually became the key to unlocking the immense parallel computing power of GPUs. CUDA plays a major role ...

Nvidia has just made a significant change: you can now run CUDA on RISC‑V processors. Previously, CUDA needed x86 or Arm CPUs to handle system tasks and coordinate GPU work. Now, RISC‑V cores can step ...

AI infrastructure company Modular has launched Mojo, a programming language for AI developers that aims to combine Python usability—and full compatibility with the Python ecosystem—with C performance.